There are many applications in which it is desirable to project patterns of light. These include displays (e.g. cinema projectors, computer displays, televisions, advertising displays—e.g. billboards, virtual reality displays etc.) as well as architectural lighting, automobile lighting (e.g. headlights, driving lights) and special effects lighting (e.g. theater stage lighting, concert lighting).
One technical problem is to provide displays capable of achieving high luminance levels. High luminance levels may be used to project light patterns having high dynamic ranges and/or to project light patterns viewable under various ambient lighting conditions, for example. With many current display technologies achieving high luminance levels is accompanied by undesirably high power consumption.
A major motivation for using light-steering in an imaging system is that peak luminance levels far above full-screen white (FSW) can be achieved. This is possible as light taken from the dark areas can be redistributed (steered) to areas that require higher luminance. Another consequence of steering light is that deeper black levels can also be reached. By extending the highlights and black levels in an image, a wider range of light levels (“increased contrast”) can be displayed simultaneously.
Light can be steered by free-form lensing. Determining a configuration for a free-form lens that will steer light to provide a desired light pattern is computationally difficult for all but very simple light patterns. Computational caustics is a field of study which relates to how refractive and/or reflective optical layers affect distribution of light.
Some approaches to computational caustics involve determining an arrangement of pre-specified discrete primitives such as planar, quadratic or Gaussian patches. Methods based on pre-specified primitives often suffer from edge effects when primitives do not meet in a compatible way.
Some alternative approaches apply optimal transportation. Optimal transportation seeks a mapping from a source to a target distribution such that a user-specified cost-function is minimized. Optimal transportation has been applied in areas as diverse as operations research and mesh processing: an optimal transport formulation is used to determine a mapping of a source intensity distribution at the lens plane to a target distribution at the image plane. This approach can achieve high-contrast and very good image quality, but comes with high-computational cost. Typical images may require hours of computation. Furthermore the computation is difficult to parallelize.
There remains a need for light projectors which can create desired light fields. There is a particular need for ways to generate desired light fields that are computationally efficient and yet provide quality reproduction of a desired light field. There is also a desire for methods and apparatus for reproducing light fields that are energy efficient.